Supervised learning algorithms like Random Forests, XGBoost, and LSTMs dominate crypto trading by predicting price directions ...

Background Early graft failure within 90 postoperative days is the leading cause of mortality after heart transplantation. Existing risk scores, based on linear regression, often struggle to capture ...

A machine learning model incorporating functional assessments predicts one-year mortality in older patients with HF and improves risk stratification beyond established scores. Functional status at ...

Machine learning models accurately predict survival after surgery for upper tract urothelial cancer, supporting personalised follow up and adjuvant treatment decisions.

BostonGene, the developer of the leading AI foundation model for tumor and immune biology, today announced another major independent validation of its AI and machine learning (ML) capabilities in a ...

Data is fundamental to hydrological modeling and water resource management; however, it remains a major challenge in many ...

Musculoskeletal (MSK) conditions drive a large share of global pain, disability, and lost productivity. Rehabilitation can be effective, but outcomes vary ...

Letters, a digital health company specializing in AI-driven hormone insight platforms, today announced the results of a U.S.

A new study published in the journal of Scientific Reports proposed a potential diagnostic tool by combining deep learning ...

The reason for this shift is simple: data gravity. The core holds the most complete, consistent and authoritative dataset ...

Researchers develop an AI tool to predict cardiometabolic multimorbidity risk in type 2 diabetes, aiding early intervention and personalised care. Find out more.